A computational stochastic procedure for solving the epidemic breathing transmission system.

Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Original Publication: London : Nature Publishing Group, copyright 2011-

Air Filters* ; Epidemics*; Colon, Sigmoid ; Databases, Factual ; Neural Networks, Computer

This work provides numerical simulations of the nonlinear breathing transmission epidemic system using the proposed stochastic scale conjugate gradient neural networks (SCGGNNs) procedure. The mathematical model categorizes the breathing transmission epidemic model into four dynamics based on a nonlinear stiff ordinary differential system: susceptible, exposed, infected, and recovered. Three different cases of the model are taken and numerically presented by applying the stochastic SCGGNNs. An activation function 'log-sigmoid' uses twenty neurons in the hidden layers. The precision of SCGGNNs is obtained by comparing the proposed and database solutions. While the negligible absolute error is performed around 10 ^-06 to 10 ^-07 , it enhances the accuracy of the scheme. The obtained results of the breathing transmission epidemic system have been provided using the training, verification, and testing procedures to reduce the mean square error. Moreover, the exactness and capability of the stochastic SCGGNNs are approved through error histograms, regression values, correlation tests, and state transitions.
(© 2023. Springer Nature Limited.)

Mahdi, A. et al. Severe acute respiratory syndrome coronavirus 2 antibody seroprevalence in Lebanon: a population-based cross-sectional study. I(JID Regions 2, 184–190 (2022). (PMID: 10.1016/j.ijregi.2022.01.011)
World Health Organization. Summary of probable SARS cases with onset of illness from 1 November 2002 to 31 July 2003. (2003) http://www.who.int/csr/sars/country/table2004_04_21/en/index.html .
World Health Organization. WHO MERS global summary and assessment of risk, July 2019 (No. WHO/MERS/RA/19.1). World Health Organization (2019).
Chowell, G. et al. Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study. BMC Med. 13(1), 1–12 (2015). (PMID: 10.1186/s12916-015-0450-0)
Mackey, T. K. & Liang, B. A. Lessons from SARS and H1N1/A: Employing a WHO–WTO forum to promote optimal economic-public health pandemic response. J. Public Health Policy 33(1), 119–130 (2012). (PMID: 10.1057/jphp.2011.5122048060)
Mobaraki, K. & Ahmadzadeh, J. Current epidemiological status of Middle East respiratory syndrome coronavirus in the world from 1.1. 2017 to 17.1. 2018: a cross-sectional study. BMC Infectious Dis., 19(1), pp.1–5. (2019).
Chan, J. F. et al. Middle East respiratory syndrome coronavirus: another zoonotic betacoronavirus causing SARS-like disease. Clin. Microbiol. Rev. 28(2), 465–522 (2015). (PMID: 10.1128/CMR.00102-14258104184402954)
Rosa, S. & Torres, D. F. Optimal control of a fractional order epidemic model with application to human respiratory syncytial virus infection. Chaos, Solitons Fractals 117, 142–149 (2018). (PMID: 10.1016/j.chaos.2018.10.021)
World Health Organization (WHO). Influenza Overview. Available from: http://www.who.int/mediacentre/factsheets/fs211/en/ .
Hafstein, S.F. A constructive converse Lyapunov theorem on asymptotic stability for nonlinear autonomous ordinary differential equations. Dynam. Syst. 20(3), 281–299 (2005).
He, J. H. Variational iteration method for autonomous ordinary differential systems. Appl. Math. Comput. 114(2–3), 115–123 (2000).
Youssef, L. et al. Knowledge, attitudes and practices towards people living with HIV/AIDS in Lebanon. PLoS One 16(3), e0249025 (2021). (PMID: 10.1371/journal.pone.0249025337650697993853)
Liang, K. Mathematical model of infection kinetics and its analysis for COVID-19, SARS and MERS. Infect. Genet. Evol. 82, 104306 (2020). (PMID: 10.1016/j.meegid.2020.104306322781477141629)
Al-Asuoad, N., Rong, L., Alaswad, S. & Shillor, M. Mathematical model and simulations of MERS outbreak: Predictions and implications for control measures. Biomath, 5(2), pp.ID-1612141. (2016).
Smith, A. F. & Oakey, R. J. Incidence and significance of errors in a patient ‘track and trigger’system during an epidemic of Legionnaires’ disease: retrospective casenote analysis. Anaesthesia 61(3), 222–228 (2006). (PMID: 10.1111/j.1365-2044.2005.04513.x16480345)
Sabir, Z., Raja, M. A. Z., Guirao, J. L. & Shoaib, M. A novel design of fractional Meyer wavelet neural networks with application to the nonlinear singular fractional Lane-Emden systems. Alexandria Eng. J. 60(2), 2641–2659 (2021). (PMID: 10.1016/j.aej.2021.01.004)
Umar, M. et al. Integrated neuro-swarm heuristic with interior-point for nonlinear SITR model for dynamics of novel COVID-19. Alexandria Eng. J. 60(3), 2811–2824 (2021). (PMID: 10.1016/j.aej.2021.01.043)
Sabir, Z. et al. Heuristic computational design of Morlet wavelet for solving the higher order singular nonlinear differential equations. Alexandria Eng. J. 60(6), 5935–5947 (2021). (PMID: 10.1016/j.aej.2021.04.001)
Mukdasai, K. et al. A numerical simulation of the fractional order Leptospirosis model using the supervise neural network. Alexandria Eng. J. 61(12), 12431–12441 (2022). (PMID: 10.1016/j.aej.2022.06.013)
Sabir, Z., Said, S.B. & Al-Mdallal, Q. A fractional order numerical study for the influenza disease mathematical model. Alexandria Eng. J. (2022).
Yaro, D., Apeanti, W. O., Akuamoah, S. W. & Lu, D. Analysis and optimal control of fractional-order transmission of a respiratory epidemic model. Int. J. Appl. Comput. Math. 5(4), 1–21 (2019). (PMID: 10.1007/s40819-019-0699-7)
Iliev, A., Kyurkchiev, N. & Markov, S. On the Approximation of the step function by some sigmoid functions. Math. Comput. Simulation 133, 223–234 (2017). (PMID: 10.1016/j.matcom.2015.11.005)
Memarian Sorkhabi, O. Geoid determination based on log sigmoid function of artificial neural networks:(a case study: Iran). J. Artificial Intell. Electric. Eng. 3(12), 18–24 (2015).
Menon, A., Mehrotra, K., Mohan, C. K. & Ranka, S. Characterization of a class of sigmoid functions with applications to neural networks. Neural Netw. 9(5), 819–835 (1996). (PMID: 10.1016/0893-6080(95)00107-712662565)
El Hayek, P., Boueri, M., Nasr, L., Aoun, C., Sayad, E. & Jallad, K. Cholera infection risks and cholera vaccine safety in pregnancy. Infect. Dis. Obstetrics and Gynecol., (2023).
Issa, J. S. A nonlinear absorber for the reflection of travelling waves in bars. Nonlinear Dynam. 108(4), 3279–3295 (2022). (PMID: 10.1007/s11071-022-07404-8)
Tian, M., El Khoury, R. & Alshater, M. M. The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies. J. Int. Financial Markets, Inst. Money 82, 101712 (2023). (PMID: 10.1016/j.intfin.2022.101712)
Kassis, M. T., Tannir, D., Toukhtarian, R. & Khazaka, R. Moments-based sensitivity analysis of x-parameters with respect to linear and nonlinear circuit components. In: 2019 IEEE 28th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS) (pp. 1–3). IEEE. (2019).
Kanbar, F., Touma, R. & Klingenberg, C. Well-balanced Central Scheme for the System of MHD Equations with Gravitational source term. arXiv preprint arXiv:2202.08584 . (2022).
Abi Younes, G. & El Khatib, N. Mathematical modeling of atherogenesis: atheroprotective role of HDL. J. Theoretical Biol. 529, 110855 (2021). (PMID: 10.1016/j.jtbi.2021.110855)
Habre, S. S. Qualitative aspects of differential equations in an inquiry-oriented course. Int. J. Math. Educ. Sci. Technol. 54(3), 351–364 (2023). (PMID: 10.1080/0020739X.2021.1954250)
Abi Younes, G. & El Khatib, N. Mathematical modeling of inflammatory processes of atherosclerosis. Math. Model. Natural Phenomena 17, 5 (2022). (PMID: 10.1051/mmnp/2022004)
Touma, R. & Saleh, M. A. Well-balanced central schemes for pollutants transport in shallow water equations. Math. Comput. Simulation 190, 1275–1293 (2021). (PMID: 10.1016/j.matcom.2021.07.021)
Younes, Y., Hallit, S. & Obeid, S. Premenstrual dysphoric disorder and childhood maltreatment, adulthood stressful life events and depression among Lebanese university students: a structural equation modeling approach. BMC Psychiatry 21(1), 1–10 (2021). (PMID: 10.1186/s12888-021-03567-7)
Habre, S. Inquiry-oriented differential equations: a guided journey of learning. Teaching Math. Appl.: Int. J. IMA 39(3), 201–212 (2020).

Date Created: 20230927 Date Completed: 20230929 Latest Revision: 20231118

20231118

PMC10533895

10.1038/s41598-023-43324-2

37758765